Future Directions of Genomics Research in Rheumatic Diseases

Yukinori Okada; Toshihiro Kishikawa; Saori Sakaue; Jun Hirata

doi:10.1016/j.rdc.2017.04.009

Future Directions of Genomics Research in Rheumatic Diseases

Rheum Dis Clin North Am. 2017 Aug;43(3):481-487. doi: 10.1016/j.rdc.2017.04.009.

Authors

Yukinori Okada¹, Toshihiro Kishikawa², Saori Sakaue³, Jun Hirata⁴

Affiliations

¹ Department of Statistical Genetics, Osaka University Graduate School of Medicine, 2-2 Yamadaoka, Suita, Osaka 565-0871, Japan. Electronic address: [email protected].
² Department of Statistical Genetics, Osaka University Graduate School of Medicine, 2-2 Yamadaoka, Suita, Osaka 565-0871, Japan; Department of Otorhinolaryngology, Head and Neck Surgery, Osaka University Graduate School of Medicine, 2-2 Yamadaoka, Suita, Osaka 565-0871, Japan.
³ Department of Statistical Genetics, Osaka University Graduate School of Medicine, 2-2 Yamadaoka, Suita, Osaka 565-0871, Japan; Department of Allergy and Rheumatology, Graduate School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan.
⁴ Department of Statistical Genetics, Osaka University Graduate School of Medicine, 2-2 Yamadaoka, Suita, Osaka 565-0871, Japan; Department of Human Genetics and Disease Diversity, Graduate School of Medical and Dental Sciences, Tokyo Medical and Dental University, 1-5-45 Yushima, Bunkyo-ku, Tokyo 113-8510, Japan; Pharmaceutical Discovery Research Laboratories, Teijin Pharma Limited, 4-3-2, Asahigaoka, Hino-shi, Tokyo 191-8512, Japan.

PMID: 28711147
DOI: 10.1016/j.rdc.2017.04.009

Abstract

Recent developments in human genome genotyping and sequencing technologies, such as genome-wide association studies and whole-genome sequencing analyses, have successfully identified several risk genes of rheumatic diseases. Fine-mapping studies using the HLA imputation method revealed that classical and non-classical HLA genes contribute to the risk of rheumatic diseases. Integration of human disease genomics with biological, medical, and clinical databases should contribute to the elucidation of disease pathogenicity and novel drug discovery. Disease risk genes identified by large-scale genetic studies are considered to be promising resources for novel drug discovery, including drug repositioning and biomarker microRNA screening for rheumatoid arthritis.

Keywords: Genome-wide association study; Human genetics; Human leukocyte antigen; Next-generation sequencing; Statistical genetics.

Publication types

Review

MeSH terms

Forecasting
Genetic Research
Genomics / trends*
Genotype
Humans
Major Histocompatibility Complex / genetics
Rheumatic Diseases / genetics*